Integrative Omics Analysis for Amyotrophic Lateral Sclerosis Public

Abstract

Introduction: Integrative omics analysis is useful for investigating the complex problems of molecular interactions in a biological system. The R package, xMWAS provides an automated workflow for integrative analysis of more than two datasets, differential network analysis, and community detection. In our study, we utilized the integrative omics analysis to explore the etiology and pathophysiology of ALS (amyotrophic lateral sclerosis). 

Method: We applied the xMWAS package to analyze three types of omics data, microbiome, metabolites and cytokines, from 10 ALS patients and 10 control subjects. We conducted integrative omics analysis for all samples and then separately for patients and control subjects. We also generate 500 bootstrap samples from our data and repeated the same analysis to investigate the significant features that are associated with ALS. 

Result: There is one more community of features in ALS compared than control subjects. The communities for ALS patients are clearer and the nodes in the communities are more closely connected. There are some 87 features whose normalized centrality indices differ by more than 0.2 between patient and controls. From the bootstrap samples, we found that there are 12 features whose centrality features are significantly different between patients and control subjects. 

Discussion: Our result about microbiome verifies previous findings in the literature that gut microbiota has a significant association with ALS disease. The centrality change for cytokines can also be explained by an increased level of blood inflammatory cytokines for ALS patients. Future studies can focus on the association between ALS etiology and gut microbiota to address the decrease in centrality. 

Table of Contents

1 Introduction.............3

2 Method.............4

2.1 DataDescription...........................4

2.2 OverviewofxMWAS.........................5

2.2.1 StageI:IntegrativeandAssociationAnalysis........5

2.2.2 StageII:GeneratetheIntegrativeNetworkGraph......6

2.2.3 StageIII:CommunityDetection...............6

2.3 Bootstrapping.............................6

2.4 AnalyzingxMWASOutput......................7

3 Result.............8

3.1 NetworkandClustersofRealData..................8

3.1.1 NetworkVisualization....................8

3.1.2 ClusterAssignmentofPatientsandcontrolsubjects.....10

3.1.3 ComparingtheCentralityofPatientsandcontrolsubjects..11

3.2 ComparingRealDatatoBootstrapSamples.............14

4 Discussion.............17

5 Appendix.............20

About this Master's Thesis

Rights statement

• Permission granted by the author to include this thesis or dissertation in this repository. All rights reserved by the author. Please contact the author for information regarding the reproduction and use of this thesis or dissertation.

School	Rollins School of Public Health
Department	Biostatistics
Subfield / Discipline	Biostatistics - MPH & MSPH
Degree	M.S.P.H.
Submission	Master's Thesis
Language	English
Research Field	Biology, Bioinformatics Biology, Biostatistics Biology, Molecular
Mot-clé	Integrative Omics Analysis ALS
Committee Chair / Thesis Advisor	Vicki Stover Hertzberg, Emory University
Committee Members	Rebecca Mans Mitchell, Emory University

Dernière modification

Primary PDF

Thumbnail	Title	Date Uploaded	Actions
	Integrative Omics Analysis for Amyotrophic Lateral Sclerosis ()	2019-04-19 10:49:00 -0400	Press to Select an action Download

Supplemental Files

Thumbnail	Title	Date Uploaded	Actions